Understanding the systemic sources of uncertainty for the management of greenhouse gas emissions in supply chains
本研究通过访谈欧洲钢铁供应链12家企业的16位受访者，识别出六类阻碍温室气体排放测量与报告的不确定性来源，并探讨信息处理机制如何帮助企业在采购、生产等环节应对这些不确定性。
Purpose This study aims to investigate how different sources of uncertainty hinder the measurement and reporting of greenhouse gas (GHG) emissions in the steel supply chain (SC). It also examines how information processing mechanisms can support SC planning and help organizations manage these uncertainties. Design/methodology/approach A qualitative approach is used, based on semi-structured interviews with 16 informants from 12 European companies operating at different positions in the steel SC, including raw material producers, manufacturers, logistics providers, wholesalers and service partners. Grounded in the organizational information processing theory, the study analyzes how uncertainty affects emissions-related information processing and planning decisions. Findings The study identifies six key sources of uncertainty that hinder emissions measurement and reporting in the steel SC. These uncertainties manifest differently across procurement, production, distribution and sales planning stages. The findings illustrate how organizations can respond through information processing mechanisms that support emissions-related planning tasks and help integrate decarbonization goals into SC decision-making. In this study, procurement planning emerged as a particularly critical stage, where targeted information processing mechanisms can help mitigate emissions-related uncertainties. Research limitations/implications This study contributes to research on sustainable SC management and SC planning by identifying key factors that generate emissions-related uncertainty and highlighting how information processing can support decarbonization efforts. Practical implications Organizations can benefit from understanding how uncertainties related to GHG emissions measurement and reporting emerge and intensify. The study suggests several information processing mechanisms that can help organizations mitigate these challenges through SC planning and inform policymaking for better carbon management. Originality/value This research contributes to the understanding of how different sources of uncertainty emerge and complicate GHG emissions measurement and reporting in the steel SC.